使用卡方自动交互检测算法对帕里亚曼交通事故受害者的特征进行分类

Manja Danova, Dina Putri, Fitria, Yenni Kurniawati, Zilrahmi
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引用次数: 0

摘要

交通事故是指机动车辆在道路上发生碰撞,导致车辆和道路基础设施受损,并可能造成相关人员的物质损失、受伤、身体损伤甚至死亡。印度尼西亚国家警察局的数据显示,2010 年至 2020 年期间,交通事故受害者人数从 147 798 人到 197 560 人不等,死亡者主要集中在 15-34 岁的人群中。交通事故受害者人数众多,对生活的各个方面都造成了负面影响,包括物质损失和对受害者身体的伤害。分类是一种技术,用于根据物体或数据的属性或特征将其归入预定义的类别。Chi-Square 自动交互检测(CHAID)是分类领域的一种方法。使用这种方法进行分类的结果表明,受害者的年龄和事故类型是影响交通事故受害者状况的最重要变量。使用混淆矩阵对模型进行评估后得出的准确率为 92%。这表明该模型在整体数据分类方面表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification the Characteristics of Traffic Accident Victims in Pariaman Using the Chi-square Automatic Interaction Detection Algorithm
Traffic accidents are incidents that occur when motor vehicles collide on the road, resulting in damage to vehicles and road infrastructure, as well as the potential for material losses, injuries, physical damage, and even death for those involved. Data from the Indonesian National Police show that the number of traffic accident victims between 2010 and 2020 ranged from 147.798 to 197.560 people, with fatalities predominantly occurring among individuals aged 15-34. The high number of traffic accident victims has negative impacts on various aspects of life, ranging from material losses to physical damage to the victims. Classification is a technique used to group objects or data into pre-defined classes or categories based on their attributes or features. One method in the field of classification is Chi-Square Automatic Interaction Detection (CHAID). The results of the classification using this method indicate that the age of the victims and the type of accident are the most significant variables influencing the condition of traffic accident victims. The evaluation of the model using a confusion matrix yielded an accuracy rate of 92%. This indicates that the model performs well in overall data classification.
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